Staff AI/ML Software Engineer

We’re not yesterday’s IT department, we're Digital Technology. The world around us keeps changing and so do we. We’re redefining what it means to be IT with a mindset centered on transformation, experience, AI-driven automation, innovation, and growth. We’re all about delivering delightful, secure customer and employee experiences that accelerate ServiceNow’s journey to become the defining enterprise software company of the 21st century. And we love co-creating, using, and highlighting our own products to do it. Ultimately, we strive to make the world work better for our employees and customers—when you work in ServiceNow Digital Technology, you work for them.The Connected Customer Experience (CCX) team creates consumer-grade digital experiences and products that help our customers and partners be successful and realize the value of their ServiceNow investment. Leveraging the latest technologies, and built on ServiceNow’s intelligent platform, we deliver a seamless, personalized experience at every step of our customers’ journey. The products we build power digital business for ServiceNow and can even become commercially available.As a Staff AI/ML Software Engineer within CCX you will build data pipeline, ML Models, secure code that's scalable and reusable. Grow our business by bringing internal products to the world and find new ways to personalize with AI/ML and simplify how employees and customers work. Implement software that empowers internal customers to extend what it can do to meet their specific needs, as our own "customer zero."What you get to do in this role:Develop real-time and batch ML models using embeddings, collaborative filtering, and deep learning.Integrate user behavior signals, session data, and content metadata to optimize relevance.Work with LLM technologies, including developing generative and embedding techniques, modern model architectures, retrieval-augmented generation (RAG), fine tuning / pre-training LLM (including parameter efficient fine-tuning), Deep reinforcement learning and evaluation benchmarksCollaborate cross-functionally with product, data, and infra teams to deploy experiments and measure impact.Optimize retrieval, filtering, and ranking algorithms in production search pipelines.Develop real-time Personalization using query Embeddings for Search RankingMonitor model performance and continuously iterate using A/B testing and offline evaluation metricsAnalyze various data and building data modeling and pipeline leveraging BigQuery data streaming or Databricks in near real-time.Distribute computing strategies in Azure, AWS or GCP Cluster, enhancing the parallel processing capabilities